Search Results for author: Yalin Wang

Found 42 papers, 10 papers with code

TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning

1 code implementation6 May 2024 Xiwen Chen, Peijie Qiu, Wenhui Zhu, Huayu Li, Hao Wang, Aristeidis Sotiras, Yalin Wang, Abolfazl Razi

Deep neural networks, including transformers and convolutional neural networks, have significantly improved multivariate time series classification (MTSC).

Multiple Instance Learning Time Series +1

Generation of Uncorrelated Residual Variables for Chemical Process Fault Diagnosis via Transfer Learning-based Input-Output Decoupled Network

no code implementations29 Apr 2024 Zhuofu Pan, Qingkai Sui, Yalin Wang, Jiang Luo, Jie Chen, Hongtian Chen

However, traditional methods exhibit limited effectiveness in modeling high-dimensional nonlinearity and big data, and the decoupling idea has not been well-valued in data-driven frameworks.

Chemical Process Fault Detection +2

Reconstructing Retinal Visual Images from 3T fMRI Data Enhanced by Unsupervised Learning

no code implementations7 Apr 2024 Yujian Xiong, Wenhui Zhu, Zhong-Lin Lu, Yalin Wang

The reconstruction of human visual inputs from brain activity, particularly through functional Magnetic Resonance Imaging (fMRI), holds promising avenues for unraveling the mechanisms of the human visual system.

Generative Adversarial Network

OmniMotionGPT: Animal Motion Generation with Limited Data

no code implementations30 Nov 2023 Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan, Bingbing Wen, Ziwei Xuan, Mitch Hill, Junjie Bai, Guo-Jun Qi, Yalin Wang

Our paper aims to generate diverse and realistic animal motion sequences from textual descriptions, without a large-scale animal text-motion dataset.

Motion Synthesis

SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification

1 code implementation31 Oct 2023 Peijie Qiu, Pan Xiao, Wenhui Zhu, Yalin Wang, Aristeidis Sotiras

In this paper, we proposed a sparsely coded MIL (SC-MIL) that addresses those two aspects at the same time by leveraging sparse dictionary learning.

Dictionary Learning Image Classification +1

PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers

1 code implementation19 Aug 2023 Wenhui Zhu, Peijie Qiu, Oana M. Dumitrascu, Yalin Wang

Multiple instance learning (MIL) was a weakly supervised learning approach that sought to assign binary class labels to collections of instances known as bags.

Multiple Instance Learning Weakly Supervised Classification +3

nnMobileNet: Rethinking CNN for Retinopathy Research

2 code implementations2 Jun 2023 Wenhui Zhu, Peijie Qiu, Xiwen Chen, Xin Li, Natasha Lepore, Oana M. Dumitrascu, Yalin Wang

Over the past few decades, convolutional neural networks (CNNs) have been at the forefront of the detection and tracking of various retinal diseases (RD).

Diabetic Retinopathy Grading

SFCNeXt: a simple fully convolutional network for effective brain age estimation with small sample size

no code implementations30 May 2023 Yu Fu, Yanyan Huang, Shunjie Dong, Yalin Wang, Tianbai Yu, Meng Niu, Cheng Zhuo

Deep neural networks (DNN) have been designed to predict the chronological age of a healthy brain from T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could serve as a valuable biomarker for the early detection of development-related or aging-related disorders.

Age Estimation

A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry

no code implementations31 Mar 2023 Jianfeng Wu, Yi Su, Yanxi Chen, Wenhui Zhu, Eric M. Reiman, Richard J. Caselli, Kewei Chen, Paul M. Thompson, Junwen Wang, Yalin Wang

Objective: To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline.

TetCNN: Convolutional Neural Networks on Tetrahedral Meshes

no code implementations8 Feb 2023 Mohammad Farazi, Zhangsihao Yang, Wenhui Zhu, Peijie Qiu, Yalin Wang

Our results show the superiority of our LBO-based convolution layer and adapted pooling over the conventionally used unitary cortical thickness, graph Laplacian, and point cloud representation.

OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing

2 code implementations6 Feb 2023 Wenhui Zhu, Peijie Qiu, Oana M. Dumitrascu, Jacob M. Sobczak, Mohammad Farazi, Zhangsihao Yang, Keshav Nandakumar, Yalin Wang

Non-mydriatic retinal color fundus photography (CFP) is widely available due to the advantage of not requiring pupillary dilation, however, is prone to poor quality due to operators, systemic imperfections, or patient-related causes.

Denoising Diabetic Retinopathy Grading +5

Improved Prediction of Beta-Amyloid and Tau Burden Using Hippocampal Surface Multivariate Morphometry Statistics and Sparse Coding

no code implementations28 Oct 2022 Jianfeng Wu, Yi Su, Wenhui Zhu, Negar Jalili Mallak, Natasha Lepore, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Kewei Chen, Yalin Wang

Experimental results suggest that amyloid/tau measurements predicted with our PASCP-MP representations are closer to the real values than the measures derived from other approaches, such as hippocampal surface area, volume, and shape morphometry features based on spherical harmonics (SPHARM).

Anisotropic Multi-Scale Graph Convolutional Network for Dense Shape Correspondence

no code implementations17 Oct 2022 Mohammad Farazi, Wenhui Zhu, Zhangsihao Yang, Yalin Wang

This paper studies 3D dense shape correspondence, a key shape analysis application in computer vision and graphics.

3D Dense Shape Correspondence

OTFPF: Optimal Transport-Based Feature Pyramid Fusion Network for Brain Age Estimation with 3D Overlapped ConvNeXt

2 code implementations10 May 2022 Yu Fu, Yanyan Huang, Yalin Wang, Shunjie Dong, Le Xue, Xunzhao Yin, Qianqian Yang, Yiyu Shi, Cheng Zhuo

In this paper, we propose an end-to-end neural network architecture, referred to as optimal transport based feature pyramid fusion (OTFPF) network, for the brain age estimation with T1 MRIs.

Age Estimation

Functional2Structural: Cross-Modality Brain Networks Representation Learning

no code implementations6 May 2022 Haoteng Tang, Xiyao Fu, Lei Guo, Yalin Wang, Scott Mackin, Olusola Ajilore, Alex Leow, Paul Thompson, Heng Huang, Liang Zhan

Since brain networks derived from functional and structural MRI describe the brain topology from different perspectives, exploring a representation that combines these cross-modality brain networks is non-trivial.

Disease Prediction Graph Learning +2

Geometry-Aware Hierarchical Bayesian Learning on Manifolds

no code implementations30 Oct 2021 Yonghui Fan, Yalin Wang

Furthermore, we incorporate the feature learning of neural networks with the feature aggregation of Bayesian models to investigate the feasibility of jointly learning on manifolds.

Gaussian Processes regression

Topological Receptive Field Model for Human Retinotopic Mapping

no code implementations15 Jun 2021 Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang

Here we propose a topological receptive field (tRF) model which imposes the topological condition when decoding retinotopic fMRI signals.

Cortical Surface Shape Analysis Based on Alexandrov Polyhedra

no code implementations ICCV 2021 Min Zhang, Yang Guo, Na lei, Zhou Zhao, Jianfeng Wu, Xiaoyin Xu, Yalin Wang, Xianfeng GU

Shape analysis has been playing an important role in early diagnosis and prognosis of neurodegenerative diseases such as Alzheimer's diseases (AD).

Developing Univariate Neurodegeneration Biomarkers with Low-Rank and Sparse Subspace Decomposition

no code implementations26 Oct 2020 Gang Wang, Qunxi Dong, Jianfeng Wu, Yi Su, Kewei Chen, Qingtang Su, Xiaofeng Zhang, Jinguang Hao, Tao Yao, Li Liu, Caiming Zhang, Richard J Caselli, Eric M Reiman, Yalin Wang

With hippocampal UMIs, the estimated minimum sample sizes needed to detect a 25$\%$ reduction in the mean annual change with 80$\%$ power and two-tailed $P=0. 05$ are 116, 279 and 387 for the longitudinal $A\beta+$ AD, $A\beta+$ mild cognitive impairment (MCI) and $A\beta+$ CU groups, respectively.

Stochastic Hybrid Combining Design for Quantized Massive MIMO Systems

no code implementations24 Aug 2020 Yalin Wang, Xihan Chen, Yunlong Cai, Lajos Hanzo

Both the power-dissipation and cost of massive multiple-input multiple-output (mMIMO) systems may be substantially reduced by using low-resolution analog-to-digital converters (LADCs) at the receivers.

Quantization Stochastic Optimization

Deep Representation Learning For Multimodal Brain Networks

no code implementations19 Jul 2020 Wen Zhang, Liang Zhan, Paul Thompson, Yalin Wang

The higher-order network mappings from brain structural networks to functional networks are learned in the node domain.

Anatomy Graph Representation Learning

Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmuller Map in Retinotopic Mapping

no code implementations25 May 2020 Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang

Although we focus on retinotopic mapping, the proposed framework is general and can be applied to process other human sensory maps.

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

4 code implementations9 Feb 2020 Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron, Arthur W. Toga, Michael W. Weiner, Frederik Barkhof, Nick C. Fox, Arman Eshaghi, Tina Toni, Marcin Salaterski, Veronika Lunina, Manon Ansart, Stanley Durrleman, Pascal Lu, Samuel Iddi, Dan Li, Wesley K. Thompson, Michael C. Donohue, Aviv Nahon, Yarden Levy, Dan Halbersberg, Mariya Cohen, Huiling Liao, Tengfei Li, Kaixian Yu, Hongtu Zhu, Jose G. Tamez-Pena, Aya Ismail, Timothy Wood, Hector Corrada Bravo, Minh Nguyen, Nanbo Sun, Jiashi Feng, B. T. Thomas Yeo, Gang Chen, Ke Qi, Shiyang Chen, Deqiang Qiu, Ionut Buciuman, Alex Kelner, Raluca Pop, Denisa Rimocea, Mostafa M. Ghazi, Mads Nielsen, Sebastien Ourselin, Lauge Sorensen, Vikram Venkatraghavan, Keli Liu, Christina Rabe, Paul Manser, Steven M. Hill, James Howlett, Zhiyue Huang, Steven Kiddle, Sach Mukherjee, Anais Rouanet, Bernd Taschler, Brian D. M. Tom, Simon R. White, Noel Faux, Suman Sedai, Javier de Velasco Oriol, Edgar E. V. Clemente, Karol Estrada, Leon Aksman, Andre Altmann, Cynthia M. Stonnington, Yalin Wang, Jianfeng Wu, Vivek Devadas, Clementine Fourrier, Lars Lau Raket, Aristeidis Sotiras, Guray Erus, Jimit Doshi, Christos Davatzikos, Jacob Vogel, Andrew Doyle, Angela Tam, Alex Diaz-Papkovich, Emmanuel Jammeh, Igor Koval, Paul Moore, Terry J. Lyons, John Gallacher, Jussi Tohka, Robert Ciszek, Bruno Jedynak, Kruti Pandya, Murat Bilgel, William Engels, Joseph Cole, Polina Golland, Stefan Klein, Daniel C. Alexander

TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease.

Alzheimer's Disease Detection Disease Prediction

Geometric Brain Surface Network For Brain Cortical Parcellation

no code implementations13 Sep 2019 Wen Zhang, Yalin Wang

Our model is a two-stage deep network which contains a coarse parcellation network with a U-shape structure and a refinement network to fine-tune the coarse results.

Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML

no code implementations20 Mar 2019 Jie Zhang, Junting Zhang, Shalini Ghosh, Dawei Li, Jingwen Zhu, Heming Zhang, Yalin Wang

Lifelong learning, the problem of continual learning where tasks arrive in sequence, has been lately attracting more attention in the computer vision community.

AutoML Continual Learning

Graph Neural Networks for User Identity Linkage

no code implementations6 Mar 2019 Wen Zhang, Kai Shu, Huan Liu, Yalin Wang

In particular, we provide a principled approach to jointly capture local and global information in the user-user social graph and propose the framework {\m}, which jointly learning user representations for user identity linkage.

MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression

no code implementations3 Feb 2019 Jie Zhang, Xiaolong Wang, Dawei Li, Shalini Ghosh, Abhishek Kolagunda, Yalin Wang

State-of-the-art deep model compression methods exploit the low-rank approximation and sparsity pruning to remove redundant parameters from a learned hidden layer.

Knowledge Distillation Model Compression

Regularized Wasserstein Means for Aligning Distributional Data

1 code implementation2 Dec 2018 Liang Mi, Wen Zhang, Yalin Wang

We propose to align distributional data from the perspective of Wasserstein means.

Domain Adaptation

Intrinsic 3D Dynamic Surface Tracking Based on Dynamic Ricci Flow and Teichmuller Map

no code implementations ICCV 2017 Xiaokang Yu, Na lei, Yalin Wang, Xianfeng GU

In this paper, we propose a novel automatic method for non-rigid 3D dynamic surface tracking with surface Ricci flow and Teichmuller map methods.

Multi-task Dictionary Learning based Convolutional Neural Network for Computer aided Diagnosis with Longitudinal Images

no code implementations31 Aug 2017 Jie Zhang, Qingyang Li, Richard J. Caselli, Jieping Ye, Yalin Wang

Firstly, we pre-train CNN on the ImageNet dataset and transfer the knowledge from the pre-trained model to the medical imaging progression representation, generating the features for different tasks.

Dictionary Learning Image Classification +1

Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions

no code implementations19 Aug 2016 Qingyang Li, Tao Yang, Liang Zhan, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang

To the best of our knowledge, this is the first successful run of the computationally intensive model selection procedure to learn a consistent model across different institutions without compromising their privacy while ranking the SNPs that may collectively affect AD.

Model Selection

Shape Analysis With Hyperbolic Wasserstein Distance

no code implementations CVPR 2016 Jie Shi, Wen Zhang, Yalin Wang

Experimental results demonstrate that our method may be used as an effective shape index, which outperforms some other standard shape measures in our AD versus healthy control classification study.

Classification General Classification

Area Preserving Brain Mapping

no code implementations CVPR 2013 Zhengyu Su, Wei Zeng, Rui Shi, Yalin Wang, Jian Sun, Xianfeng GU

Experimental results on caudate nucleus surface mapping and cortical surface mapping demonstrate the efficacy and efficiency of the proposed method.

Hyperbolic Harmonic Mapping for Constrained Brain Surface Registration

no code implementations CVPR 2013 Rui Shi, Wei Zeng, Zhengyu Su, Hanna Damasio, Zhonglin Lu, Yalin Wang, Shing-Tung Yau, Xianfeng GU

This work conquer this problem by changing the Riemannian metric on the target surface to a hyperbolic metric, so that the harmonic mapping is guaranteed to be a diffeomorphism under landmark constraints.

Cannot find the paper you are looking for? You can Submit a new open access paper.